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  • 1
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    Keywords: Water vapor, Atmospheric. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (284 pages)
    Edition: 1st ed.
    ISBN: 9783030289065
    DDC: 551.517
    Language: English
    Note: Intro -- Foreword -- Preface -- Acknowledgements -- Contents -- List of Figures -- List of Tables -- Contributors -- 1: Introduction to Atmospheric Rivers -- 1.1 A Brief History of AR Science -- 1.1.1 The 1970s -- 1.1.2 The 1980s -- 1.1.3 The 1990s -- 1.1.4 The 2000s -- AR Impacts: Precipitation, Flooding, and Water Supply -- 1.1.5 2010 and Beyond -- The California AR Observation Network -- The Forecasting Challenge -- AR Duration Found to Help Modulate AR Impacts -- 1.1.6 ARs and Global Climate Change -- 1.2 Structure of This Book -- References -- 2: Structure, Process, and Mechanism -- 2.1 Introduction -- 2.2 Structure of ARs -- 2.2.1 Definition of the Term "Atmospheric River" -- 2.2.2 Water Vapor Transport and the Vertical and Horizontal Structure of ARs -- Direct Observations of Water Vapor Transport -- Observations of Vertical and Horizontal Structure -- Representativeness of Airborne Observations and Typical Range of Key Characteristics -- 2.3 WCBs and TMEs and Their Relationship to ARs -- 2.3.1 Concepts of TMEs, ARs, and WCBs -- 2.3.2 Climatologies -- 2.3.3 Linkages Among the Three Feature Categories -- 2.3.4 Summary -- 2.4 Water Vapor Transport in ARs -- 2.4.1 Moisture Budget During the AR Life Cycle -- 2.4.2 Horizontal and Vertical Moisture Transport and AR Maintenance -- 2.4.3 Methods for Obtaining an AR Water Budget -- 2.4.4 Conclusions, Implications, and Future Directions -- 2.5 ARs and Extratropical Dynamics -- 2.5.1 Mid-Latitude Storm Track and Cyclogenesis -- 2.5.2 Mid-Latitude Cyclones and ARs -- 2.5.3 Linking Extratropical Dynamics to Hydrometeorological Effects -- 2.5.4 Summary -- 2.6 A Case Study Example -- References -- 3: Observing and Detecting Atmospheric Rivers -- 3.1 Introduction -- 3.2 Satellite Observations of ARs -- 3.2.1 Microwave Radiometry: SSM/I -- 3.2.2 Radio Occultation: COSMIC. , 3.2.3 Satellite-Based Cloud and Precipitation Radars: CloudSat and GPM -- 3.3 AR Observatories -- 3.3.1 AR Characteristics Not Readily Observed Using Traditional Meteorological Methods -- The Low-Level Jet and the "Controlling Layer" -- Temporal and Horizontal Spatial Scales of ARs Relative to the Operational Radiosonde Network -- Summary of the Gaps -- 3.3.2 ARO Instrumentation -- Doppler Wind Profilers -- Surface Meteorology Towers -- Global Positioning System/Meterology (GPS/ MET) -- 3.3.3 The ARO Water Vapor Flux Tool -- 3.3.4 The US West Coast ARO "Picket Fence" -- 3.4 Network Observations: Monitoring ARs over California -- 3.4.1 AR Observatories (AROs) -- 3.4.2 Snow-Level Radar -- 3.4.3 Integrated Water Vapor (GPS/MET) -- 3.4.4 Soil Moisture -- 3.5 Field Campaigns and Experiments -- 3.5.1 CALJET -- 3.5.2 PACJET -- 3.5.3 HMT -- 3.5.4 Ghost Nets -- 3.5.5 CalWater-1 -- 3.5.6 WISPAR -- 3.5.7 CalWater-2 -- 3.5.8 ENRR and SHOUT -- 3.5.9 NAWDEX -- 3.5.10 AR Reconnaissance -- 3.5.11 Synthesis of Airborne Cross-Sections Across ARs into a Composite of AR Structure and TIVT -- 3.6 ARs in Reanalyses -- 3.7 AR Identification -- References -- 4: Global and Regional Perspectives -- 4.1 Introduction -- 4.2 Global Climatology -- 4.2.1 AR Detection Method and Justification -- 4.2.2 AR Frequency and IVT -- 4.2.3 AR Landfall Frequency -- 4.2.4 AR Duration -- 4.2.5 AR Precipitation Fraction -- 4.2.6 Seasonality -- 4.2.7 Summary of Sect. 4.2 -- 4.3 Climate Modulation -- 4.3.1 El Niño-Southern Oscillation -- 4.3.2 Madden-Julian Oscillation -- 4.3.3 Arctic Oscillation -- 4.3.4 Pacific/North American Pattern -- 4.3.5 Summary of Sect. 4.3 -- 4.4 ARs along the North American West Coast -- 4.4.1 Summary of Sect. 4.4 -- 4.5 Inland-Penetrating ARs Over the Western United States -- 4.5.1 Summary of Sect. 4.5. , 4.6 ARs in the Southeastern US -- 4.6.1 Summary of Sect. 4.6 -- 4.7 Europe -- 4.7.1 Summary of Sect. 4.7 -- 4.8 Southern South America -- 4.8.1 Summary of Sect. 4.8 -- 4.9 ARs in the Polar Regions -- 4.9.1 Arctic -- 4.9.2 Antarctic -- 4.9.3 Summary of Sect. 4.9 -- References -- 5: Effects of Atmospheric Rivers -- 5.1 Introduction -- 5.2 ARs and Orographic Precipitation -- 5.2.1 Precipitation Formation -- 5.2.2 Orographic Precipitation Enhancement -- 5.3 ARs, Floods and Water Resources -- 5.3.1 Flooding -- 5.3.2 Water Resources -- 5.4 Other Effects of ARs -- 5.4.1 Aquatic Ecosystems -- Estuarine Effects -- 5.4.2 Terrestrial Landscapes -- 5.4.3 Surface Winds -- 5.4.4 Coastal Sea Level -- 5.5 Regional Perspectives on AR Effects -- 5.5.1 North America -- 5.5.2 Europe -- 5.5.3 South America -- 5.5.4 New Zealand -- 5.5.5 Polar Regions -- Antarctica -- Arctic -- 5.6 Summary and Characteristics that Control AR Effects -- 5.6.1 Meteorological Characteristics -- IVT Rates -- IWV Amounts -- Rates of AR Translation Across the Landscape -- Air Temperature -- Atmospheric Stability -- Elevation of the AR Jet -- Barrier Jets -- 5.6.2 Land Characteristics -- Antecedent Conditions -- Terrain Characteristics -- Drainage Density -- Bedrock and Soil Type -- Land Use -- 5.6.3 Some Examples -- 5.7 Looking Forward -- References -- 6: Atmospheric River Modeling: Forecasts, Climate Simulations, and Climate Projections -- 6.1 Introduction -- 6.2 Forecasting ARs -- 6.2.1 An Ingredient-Based Approach to Forecasting ARs -- 6.2.2 Evaluating Forecasts of Landfalling ARs -- 6.2.3 AR Analysis and Forecasting Tools -- 6.3 Simulating ARs -- 6.3.1 Regional Models -- 6.3.2 Global Models -- Evaluating Model Performance for AR Simulations Based on Payne and Magnusdottir (2015) -- 6.4 Climate Projections of ARs. , 6.5 Summary and Emerging Directions -- References -- 7: Applications of Knowledge and Predictions of Atmospheric Rivers -- 7.1 Introduction -- 7.2 US Army Corps of Engineers: ARs and Flood Risk Management -- 7.2.1 A Case History -- 7.2.2 Real-World AR Issues -- Where Will the AR Strike? Stalls, Shifts, Trajectories, and Drainage Basins -- Forecasts or Observations? -- Drafting Floodwaters -- Flood Risks vs. Water Supply -- AR Seasonality -- Probable Maximum Precipitation (PMP) Estimates -- Forecast Improvements -- Next Steps -- 7.3 Forecast Informed Reservoir Operations, Lake Mendocino Pilot Study -- 7.4 ARs Use in Flood Planning in California -- 7.5 AR Science, Natural Hazards Risk Reduction, and ARkStorm -- 7.6 Scales That Communicate AR Intensity and Impacts -- 7.6.1 ECMWF's Extreme Forecast Index for Water Vapor Transport -- 7.6.2 A Scale for Atmospheric River Strength and Impacts -- References -- 8: The Future of Atmospheric River Research and Applications -- 8.1 Introduction -- 8.1.1 F. Martin Ralph (Western US Weather Science -- Regional Water Applications Development) -- 8.1.2 Duane E. Waliser (Global Atmospheric Science -- Satellite and Reanalysis Applications) -- 8.1.3 Jonathan J. Rutz (Weather Forecast Improvement -- AR Detection) -- 8.1.4 Michael D. Dettinger (Hydrologic Science and Applications -- Climate Change Diagnostics) -- 8.2 Observational Gaps -- 8.2.1 Ground Based -- 8.2.2 Airborne Physical Process Studies -- 8.2.3 A Vision for AR Reconnaissance -- Proof of Concept: Data Collection -- Proof of Concept: Data Assimilation and Modeling -- Anticipated Outcomes of AR Recon Data, Modeling, and Assimilation -- Vision of Potential Operational Implementation of AR Recon -- 8.2.4 Satellite -- 8.2.5 Reanalyses: Evaluations and Gaps to Be Addressed to Support AR Science and Applications. , 8.3 Emerging Directions in AR Physical Processes Research -- 8.3.1 Polar Processes Associated with ARs -- 8.3.2 Atmospheric Water Budget and Moist Processes -- 8.3.3 Terrestrial Hydrology and Water Budget -- 8.4 Communicating and Applying AR Information -- 8.4.1 How AR Science Affects Operations in the US National Weather Service's Western Region -- 8.4.2 Communicating ARs to Broader Technical and Lay Communities -- 8.4.3 Developing New AR Forecast Methods and Displays -- 8.4.4 Intercomparisons of AR Tracking Methods -- 8.4.5 Forecast-Informed Reservoir Operations (FIRO) -- 8.5 Exploring Subseasonal-to-Seasonal (S2S) Prediction of ARs -- 8.5.1 Western Water Management Requests Improved Precipitation Outlooks -- 8.5.2 Large-Scale Processes/Short-Term Climate Variability that Modulate ARs -- 8.5.3 The Promise and Challenge of Creating S2S Precipitation Outlooks for the West -- 8.6 Concluding Remarks -- References -- Index.
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  • 2
    Publication Date: 2023-01-30
    Description: The AR "dust score" characterizes the dustiness of the environment associated with ARs that made landfall along the west coast of the U.S. between 2001 and 2018 using satellite-based observations. The AR dust score is calculated from the average of dust aerosol optical depth within the horizontal boundaries of the landfalling AR, as defined by the Rutz AR catalogue. This dataset has been used to investigate how often dust is present in the surroundings of ARs along the U.S. west coast, as dust can impact cloud microphysics and precipitation from these storms. Further information describing the calculation of an AR dust score can be found in Voss et al. (2020) (doi:10.1175/JCLI-D-20-0059.1).
    Keywords: aerosol; atmospheric river; DATE/TIME; Defined by the Rutz AR catalogue; dust; dust score; Dust score; Pixels within atmospheric rivers feature
    Type: Dataset
    Format: text/tab-separated-values, 13140 data points
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  • 3
    Publication Date: 2022-05-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Sun, R., Subramanian, A. C., Cornuelle, B. D., Mazloff, M. R., Miller, A. J., Ralph, F. M., Seo, H., & Hoteit, I. The role of air-sea interactions in atmospheric rivers: Case studies using the SKRIPS regional coupled model. Journal of Geophysical Research: Atmospheres, 126(6), (2021): e2020JD032885, https://doi.org/10.1029/2020JD032885.
    Description: Atmospheric rivers (ARs) play a key role in California's water supply and are responsible for most of the extreme precipitation and major flooding along the west coast of North America. Given the high societal impact, it is critical to improve our understanding and prediction of ARs. This study uses a regional coupled ocean–atmosphere modeling system to make hindcasts of ARs up to 14 days. Two groups of coupled runs are highlighted in the comparison: (1) ARs occurring during times with strong sea surface temperature (SST) cooling and (2) ARs occurring during times with weak SST cooling. During the events with strong SST cooling, the coupled model simulates strong upward air–sea heat fluxes associated with ARs; on the other hand, when the SST cooling is weak, the coupled model simulates downward air–sea heat fluxes in the AR region. Validation data shows that the coupled model skillfully reproduces the evolving SST, as well as the surface turbulent heat transfers between the ocean and atmosphere. The roles of air–sea interactions in AR events are investigated by comparing coupled model hindcasts to hindcasts made using persistent SST. To evaluate the influence of the ocean on ARs we analyze two representative variables of AR intensity, the vertically integrated water vapor (IWV) and integrated vapor transport (IVT). During strong SST cooling AR events the simulated IWV is improved by about 12% in the coupled run at lead times greater than one week. For IVT, which is about twice more variable, the improvement in the coupled run is about 5%.
    Description: The authors gratefully acknowledge the research funding (grant number: OSR-2-16-RPP-3268.02) from KAUST (King Abdullah University of Science and Technology). The authors also appreciate the computational resources on supercomputer Shaheen II and the assistance provided by KAUST Supercomputer Laboratory. Additional funding from the NSF (OCE2022846, and OCE2022868) and the National Oceanic and Atmospheric Administration (MAPP NA17OAR4310106 and NA17OAR4310255) is also greatly appreciated. This study is also supported by the U.S. Army Corps of Engineers (USACE)-Cooperative Ecosystem Studies Unit (CESU) as part of Forecast Informed Reservoir Operations (FIRO) under grant W912HZ-15-2-0019. The authors thank Caroline Papadopoulos for important technical support when installing software and using the Shaheen II cluster.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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